期刊
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY
卷 274, 期 -, 页码 1-11出版社
ELSEVIER
DOI: 10.1016/j.ijfoodmicro.2018.02.023
关键词
Core genome multilocus sequence typing (cgMLST); Single nucleotide polymorphisms (SNPs); Whole-genome sequencing (wgs); Salmonella; Outbreak; Phylogeny
资金
- National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Gastrointestinal Infections at University of Liverpool [NIHR HPRU-2012-10038]
- Public Health England (PHE)
- University of East Anglia
- University of Oxford
- Quadram Institute
- Wellcome Trust [202792/Z/16/Z]
- Biotechnology and Biological Sciences Research Council [BB/L020319/1]
- BBSRC [BB/L020319/1] Funding Source: UKRI
Multi-country outbreaks of foodbome bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enteriea (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMIST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MIST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions.
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